Multiple hypothesis testing is concerned with maintaining low the number of false positives when testing several hypotheses simultaneously, while achieving a number of false negatives as small as possible. Procedures should be distribution free and robust with respect to known or possibly unknown dependence. This thesis is related to modern approaches. After a review of the most recent developments, we prove robustness of certain procedures under weak dependence. We then propose a new class of procedures and estimators for the proportion of false null hypotheses, i.e., the strength of the...
Multiple hypothesis testing is concerned with maintaining low the number of false positives when testing several hypotheses simultaneously, while achi...
Francesco Bartolucci Alessio Farcomeni Fulvia Pennoni
Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB(r) routines used for the examples are available on the authors' website.
The book provides you with the essential background on latent variable models, particularly the latent class model. It...
Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.
The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and...
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and us...
